Image fusion of the Terahertz-visual NAECON Grand Challenge data

Terahertz (THz) sensing has been developed over the past three decades for concealed weapons detection, medical imaging, and non-destructive evaluation; however methods for THz image exploitation have not been well reported. We test a multiscale image fusion algorithm for the 2011 IEEE National Aerospace and Electronics Conf. (NAECON) Grand Challenge which consists of Terahertz (THz) and visual images. The study consists of image characterization (signals distribution), image processing (data fusion), and image analysis (edge detection). We found that THz image characterization did not necessarily follow a distinct Gaussian distribution, THz imagery fusion with visual data supported target detection, and that image analysis enhanced target assessment. For the initial experiment, we assess the target segmentation through edge detection, image fusion results, and image fusion quality assessment. The preliminary image exploitation and fusion results can further develop THz collection over clothing-obscured concealed weapons imaging, parameter optimization, and targeting evaluation.